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Record W2798017140 · doi:10.61673/ren.2018.429

DETERMINANTES DAS ESCOLHAS DE TRABALHO E ESTUDO NA POPULAÇÃO INFANTIL EM PERNAMBUCO

2018· article· pt· W2798017140 on OpenAlexaff
Diogo Brito Sobreira, Gabriel Alves de Sampaio Morais, Andréa Ferreira da Silva, Lorena Vieira Costa

Bibliographic record

VenueRevista Econômica do Nordeste · 2018
Typearticle
Languagept
FieldSocial Sciences
TopicPoverty, Education, and Child Welfare
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsHumanitiesPsychologyPhilosophy

Abstract

fetched live from OpenAlex

O trabalho infantil é um problema social com consequências que se manifestam no curto prazo, comprometendo a saúde e o desempenho escolar das crianças, assim como no longo prazo uma vez que relaciona-se a menores salários na vida adulta. Assim, esta pesquisa objetiva analisar como os fatores de background familiar influenciam a decisão das famílias no trabalho e frequência escolar das crianças no estado do Pernambuco, utilizando microdados da Pesquisa Nacional por Amostra de Domicílio (PNAD) para o ano de 2014. Adotou-se o método probit bivariado por considerar que a decisão de trabalhar e estudar são interdependentes. Os resultados apontam que a idade da criança impacta positivamente a decisão de trabalhar e negativamente a de estudar. Além disso, o background familiar, especificamente, o aumento dos anos de estudo da mãe e renda do chefe da família, reduzem as chances das crianças pertencerem ao grupo das que nem trabalham e nem estudam, que só trabalham ou que trabalham e estudam. Entretanto, aumentam as chances das crianças só estudarem. Nesse sentido, o artigo traz resultados importantes que podem auxiliar na formatação de políticas públicas para erradicar o trabalho infantil e combate à pobreza de longo prazo.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.737
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.321
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueRevista Econômica do NordesteSame topicPoverty, Education, and Child WelfareFrench-language works237,207